The Development of Dominance Stripes and Orientation Maps in a Self-Organising Visual Cortex Network (VICON)

12/16/2010
by   Stephen Luttrell, et al.
0

A self-organising neural network is presented that is based on a rigorous Bayesian analysis of the information contained in individual neural firing events. This leads to a visual cortex network (VICON) that has many of the properties emerge when a mammalian visual cortex is exposed to data arriving from two imaging sensors (i.e. the two retinae), such as dominance stripes and orientation maps.

READ FULL TEXT

page 19

page 21

page 22

page 23

page 25

research
09/27/2018

A rotation-equivariant convolutional neural network model of primary visual cortex

Classical models describe primary visual cortex (V1) as a filter bank of...
research
12/24/2012

Reconstructing Self Organizing Maps as Spider Graphs for better visual interpretation of large unstructured datasets

Self-Organizing Maps (SOM) are popular unsupervised artificial neural ne...
research
07/06/2021

Polarized skylight orientation determination artificial neural network

This paper proposes an artificial neural network to determine orientatio...
research
11/14/2021

Choriented Maps: Visualizing SDG Data on Mobile Devices

Choropleth maps and graduated symbol maps are often used to visualize qu...
research
09/17/2023

Integration of geoelectric and geochemical data using Self-Organizing Maps (SOM) to characterize a landfill

Leachates from garbage dumps can significantly compromise their surround...
research
08/29/2022

Evolving Label Usage within Generation Z when Self-Describing Sexual Orientation

Evaluating change in ranked term importance in a growing corpus is a pow...
research
12/19/2010

A Self-Organising Neural Network for Processing Data from Multiple Sensors

This paper shows how a folded Markov chain network can be applied to the...

Please sign up or login with your details

Forgot password? Click here to reset